Specialized Stroke Services: A Meta-Analysis Comparing Three Models of Care
Bibliographic record
Abstract
BACKGROUND: Using previously published data, the purpose of this study was to identify and discriminate between three different forms of inpatient stroke care based on timing and duration of treatment and to compare the results of clinically important outcomes. METHODS: Randomized controlled trials, including a recent review of inpatient stroke unit/rehabilitation care, were identified and grouped into three models of care as follows: (a) acute stroke unit care (patients admitted within 36 h of stroke onset and remaining for up to 2 weeks; n = 5), (b) units combining acute and rehabilitative care (combined; n = 4), and (c) rehabilitation units where patients were transferred onto the service approximately 2 weeks following stroke (post-acute; n = 5). Pooled analyses for the outcomes of mortality, combined death and dependency and length of hospital stay were calculated for each model of care, compared to conventional care. RESULTS: All three models of care were associated with significant reductions in the odds of combined death and dependency; however, acute stroke units were not associated with significant reductions in mortality when this outcome was analyzed separately (OR 0.80; 95% CI: 0.61-1.03). Post-acute stroke units were associated with the greatest reduction in the odds of mortality (OR 0.60; 95% CI: 0.44-0.81). Significant reductions in length of hospital stay were associated with combined stroke units only (weighted mean difference -14 days; 95% CI: -27 to -2). CONCLUSIONS: Overall, specialized stroke services were associated with significant reductions in mortality, death and dependency and length of hospital stay although not every model of care was associated with equal benefit.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.040 | 0.062 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.021 | 0.102 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".